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A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis

Overview of attention for article published in Frontiers in Microbiology, June 2017
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103 Mendeley
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Title
A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis
Published in
Frontiers in Microbiology, June 2017
DOI 10.3389/fmicb.2017.00996
Pubmed ID
Authors

Jean-Guillaume Emond-Rheault, Julie Jeukens, Luca Freschi, Irena Kukavica-Ibrulj, Brian Boyle, Marie-Josée Dupont, Anna Colavecchio, Virginie Barrere, Brigitte Cadieux, Gitanjali Arya, Sadjia Bekal, Chrystal Berry, Elton Burnett, Camille Cavestri, Travis K. Chapin, Alanna Crouse, France Daigle, Michelle D. Danyluk, Pascal Delaquis, Ken Dewar, Florence Doualla-Bell, Ismail Fliss, Karen Fong, Eric Fournier, Eelco Franz, Rafael Garduno, Alexander Gill, Samantha Gruenheid, Linda Harris, Carol B. Huang, Hongsheng Huang, Roger Johnson, Yann Joly, Maud Kerhoas, Nguyet Kong, Gisèle Lapointe, Line Larivière, Stéphanie Loignon, Danielle Malo, Sylvain Moineau, Walid Mottawea, Kakali Mukhopadhyay, Céline Nadon, John Nash, Ida Ngueng Feze, Dele Ogunremi, Ann Perets, Ana V. Pilar, Aleisha R. Reimer, James Robertson, John Rohde, Kenneth E. Sanderson, Lingqiao Song, Roger Stephan, Sandeep Tamber, Paul Thomassin, Denise Tremblay, Valentine Usongo, Caroline Vincent, Siyun Wang, Joel T. Weadge, Martin Wiedmann, Lucas Wijnands, Emily D. Wilson, Thomas Wittum, Catherine Yoshida, Khadija Youfsi, Lei Zhu, Bart C. Weimer, Lawrence Goodridge, Roger C. Levesque

Abstract

The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 103 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 20%
Student > Ph. D. Student 15 15%
Student > Master 15 15%
Professor 10 10%
Student > Bachelor 5 5%
Other 16 16%
Unknown 21 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 32%
Biochemistry, Genetics and Molecular Biology 10 10%
Immunology and Microbiology 9 9%
Economics, Econometrics and Finance 4 4%
Nursing and Health Professions 3 3%
Other 13 13%
Unknown 31 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 June 2017.
All research outputs
#15,131,896
of 24,464,848 outputs
Outputs from Frontiers in Microbiology
#12,739
of 27,725 outputs
Outputs of similar age
#176,207
of 321,727 outputs
Outputs of similar age from Frontiers in Microbiology
#307
of 532 outputs
Altmetric has tracked 24,464,848 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 27,725 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 321,727 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 532 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.